Development of an artificial vision algorithm with neural networks for the detection of cracks in concrete structures
DOI:
https://doi.org/10.18050/ingnosis.v9i1.3171Keywords:
Fissures, image processing, artificial visionAbstract
An algorithm was developed to detect fissures in concrete structures applying artificial vision and image processing techniques. The algorithm centers its operation on an Asus laptop with an Intel Core i5 processor and Windows 11 64-bit, which, connected to a cell phone camera with the iVCam application, acquires images of the concrete applying the basic photography technique. The acquired images are processed within the laptop and statistical methods and artificial vision are used to detect anomalies present in concrete or concrete structures, such as cracks in grouting. From the tests carried out with the algorithm, a system efficiency of 93.02% was obtained as a result. It is concluded that the implementation of the algorithm improves the quality and good condition of the concrete at the same time allows a greater efficiency of the process, carrying out daily production control in a stored database.
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Copyright (c) 2024 Kevin Rubén Bartra Aguilar, Carlos Wilfredo Montenegro Honores, Carlos Andrés Pretell Ramirez, Raúl Alfredo Méndez Parodi
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